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from stl import mesh | |
from mpl_toolkits import mplot3d | |
from matplotlib import pyplot as plt | |
from typing import List, Tuple | |
def generate_mesh_images(file_path: str, viewing_angles: List[Tuple[int, int]], output_prefix: str = 'mesh_') -> List[str]: | |
""" | |
Generate images of an STL file from different viewing angles and return their file paths. | |
Args: | |
file_path (str): Path to the STL file. | |
viewing_angles (List[Tuple[int, int]]): List of tuples containing the elevation and azimuth angles for viewing. | |
output_prefix (str, optional): Prefix for the output image filenames. Defaults to 'mesh_'. | |
Returns: | |
List[str]: List of file paths of the generated images. | |
""" | |
# Load the STL file | |
your_mesh = mesh.Mesh.from_file(file_path) | |
# List to store the file paths of the generated images | |
image_paths = [] | |
# Iterate over each viewing angle and generate an image | |
for i, (elev, azim) in enumerate(viewing_angles, start=1): | |
# Create a new plot with a larger figure size | |
fig = plt.figure(figsize=(10, 10)) | |
ax = fig.add_subplot(111, projection='3d') | |
# Add the STL file to the plot | |
ax.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors)) | |
# Calculate the limits of the mesh | |
max_dim = max(your_mesh.points.flatten()) | |
min_dim = min(your_mesh.points.flatten()) | |
# Set the limits of the plot | |
ax.set_xlim([min_dim, max_dim]) | |
ax.set_ylim([min_dim, max_dim]) | |
ax.set_zlim([min_dim, max_dim]) | |
# Set the viewing angle | |
ax.view_init(elev=elev, azim=azim) | |
# Save the plot as an image | |
image_path = f'{output_prefix}{i}.png' | |
plt.savefig(image_path) | |
image_paths.append(image_path) | |
# Close the plot to avoid memory leaks | |
plt.close() | |
return image_paths | |
if __name__ == "__main__": | |
# Example usage: | |
# file_path = 'sample_data.stl' | |
viewing_angles = [(30, 45), (60, 90), (45, 135)] | |
# generate_mesh_images(file_path, viewing_angles) | |